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sympy

Skill3 starsChanged 8 months agoMITView on GitHub

Use symbolic math in Python for CS research and algorithm work. Use when deriving formulas, simplifying objectives, solving recurrences or equations, manipulating matrices symbolically, generating exact expressions, or turning mathematical derivations into executable code.

13 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

5 rules. 0 are common, 5 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 13 edited versions we read keep these.

  • 5

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when exact symbolic reasoning is more valuable than numerical approximation.

    line 8
  2. Distinctive:

    Keep expressions symbolic as long as that improves insight.

    line 29
  3. Distinctive:

    Prefer exact simplification when comparing formulations.

    line 31
  4. Distinctive:

    Document assumptions on domains, positivity, or integrality when they affect the result.

    line 32
  5. Distinctive:

    When the user asks for symbolic help without a specific format, return:

    line 36

“Common” is measured: kept by at least 6 in 10 of the 13 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

SymPy

Use this skill when exact symbolic reasoning is more valuable than numerical approximation.

Common CS Uses

  • derive loss functions or gradients
  • simplify probabilistic or optimization expressions
  • solve recurrences or closed forms in algorithm analysis
  • manipulate matrices symbolically
  • generate LaTeX for proofs, notes, or papers
  • generate code from symbolic expressions

Local References

  • references/core-capabilities.md
  • references/matrices-linear-algebra.md
  • references/code-generation-printing.md
  • references/advanced-topics.md
  • references/physics-mechanics.md only if the task truly needs it

Working Rules

  • Keep expressions symbolic as long as that improves insight.
  • Switch to numerical evaluation only after the derivation is stable.
  • Prefer exact simplification when comparing formulations.
  • Document assumptions on domains, positivity, or integrality when they affect the result.

Default Output

When the user asks for symbolic help without a specific format, return:

  1. the symbolic setup
  2. the derived or simplified result
  3. assumptions used
  4. code or LaTeX if that helps downstream use

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